Marine Protected Area Management Effectiveness: Progress and ...

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518 A. P. Maypa et al.
Figure 4. MDS plot of the 56 MPAs and 3 proposed case study sites in the Central Visayas with target
fish densities, % live hard coral cover (LHC), and MPA size as the major contributing factors. Two
major groups (1: A, B and 2: C, D) and 12 subgroups are generated. Target fish density classification
followed that of Hilomen et al. (2000) and for LHC, Gomez et al. (2004) was used (color figure
available online).
(Figure 4). A SIMPER analysis revealed that target fish densities, LHC and MPA size are
the main contributing factors (90%) for the groupings that resulted. MPA age was excluded
at 90%. Groupings of MPAs formed with generally low to high target fish densities and
fair to excellent LHC and among MPAs with very low target fish densities but LHC ranges
from poor to excellent.
This information on reef parameters allowed us to assess the impacts of local capacity
building on MPA coral reef health using MPA ratings as a measure. When comparing the
MPA ratings of the two major groups (Figure 4), the average MPA rating in group 1 (groups
A and B: low to high target fish densities and fair to excellent LHC) was significantly
higher (Mann– Whitney U Test, W = 690, p = .0142) compared to group 2 (groups C and
D: very low target fish densities, LHC ranges from poor to excellent). Median MPA rating
for Group A is at 4 (sustained), while 3 (enforced) for Group B. These results indicate
that MPAs that have high MPA management ratings are likely to have better reef health
conditions in terms of%LHC and fish density.
Discussion
One outcome of the Visayan case study comparing biophysical results and management
effectiveness ratings is that LHC and target fish densities as measures of management and
governance effectiveness may not be able to provide a complete picture without including